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PiperOrigin-RevId: 529495239
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@@ -4,8 +4,6 @@ title: Home
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nav_order: 1
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---
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----
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**Attention:** *Thanks for your interest in MediaPipe! We have moved to
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@@ -14,86 +12,111 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
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*This notice and web page will be removed on June 1, 2023.*
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----
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<br><br><br><br><br><br><br><br><br><br>
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<br><br><br><br><br><br><br><br><br><br>
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<br><br><br><br><br><br><br><br><br><br>
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**Attention**: MediaPipe Solutions Preview is an early release. [Learn
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more](https://developers.google.com/mediapipe/solutions/about#notice).
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--------------------------------------------------------------------------------
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**On-device machine learning for everyone**
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## Live ML anywhere
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Delight your customers with innovative machine learning features. MediaPipe
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contains everything that you need to customize and deploy to mobile (Android,
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iOS), web, desktop, edge devices, and IoT, effortlessly.
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[MediaPipe](https://google.github.io/mediapipe/) offers cross-platform, customizable
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ML solutions for live and streaming media.
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* [See demos](https://goo.gle/mediapipe-studio)
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* [Learn more](https://developers.google.com/mediapipe/solutions)
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 | 
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:------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------:
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***End-to-End acceleration***: *Built-in fast ML inference and processing accelerated even on common hardware* | ***Build once, deploy anywhere***: *Unified solution works across Android, iOS, desktop/cloud, web and IoT*
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 | 
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***Ready-to-use solutions***: *Cutting-edge ML solutions demonstrating full power of the framework* | ***Free and open source***: *Framework and solutions both under Apache 2.0, fully extensible and customizable*
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## Get started
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----
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You can get started with MediaPipe Solutions by by checking out any of the
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developer guides for
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[vision](https://developers.google.com/mediapipe/solutions/vision/object_detector),
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[text](https://developers.google.com/mediapipe/solutions/text/text_classifier),
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and
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[audio](https://developers.google.com/mediapipe/solutions/audio/audio_classifier)
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tasks. If you need help setting up a development environment for use with
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MediaPipe Tasks, check out the setup guides for
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[Android](https://developers.google.com/mediapipe/solutions/setup_android), [web
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apps](https://developers.google.com/mediapipe/solutions/setup_web), and
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[Python](https://developers.google.com/mediapipe/solutions/setup_python).
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## ML solutions in MediaPipe
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## Solutions
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Face Detection | Face Mesh | Iris | Hands | Pose | Holistic
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:----------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :------:
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[](https://google.github.io/mediapipe/solutions/face_detection) | [](https://google.github.io/mediapipe/solutions/face_mesh) | [](https://google.github.io/mediapipe/solutions/iris) | [](https://google.github.io/mediapipe/solutions/hands) | [](https://google.github.io/mediapipe/solutions/pose) | [](https://google.github.io/mediapipe/solutions/holistic)
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MediaPipe Solutions provides a suite of libraries and tools for you to quickly
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apply artificial intelligence (AI) and machine learning (ML) techniques in your
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applications. You can plug these solutions into your applications immediately,
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customize them to your needs, and use them across multiple development
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platforms. MediaPipe Solutions is part of the MediaPipe [open source
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project](https://github.com/google/mediapipe), so you can further customize the
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solutions code to meet your application needs.
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Hair Segmentation | Object Detection | Box Tracking | Instant Motion Tracking | Objectron | KNIFT
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:-------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------: | :---:
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[](https://google.github.io/mediapipe/solutions/hair_segmentation) | [](https://google.github.io/mediapipe/solutions/object_detection) | [](https://google.github.io/mediapipe/solutions/box_tracking) | [](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | [](https://google.github.io/mediapipe/solutions/objectron) | [](https://google.github.io/mediapipe/solutions/knift)
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These libraries and resources provide the core functionality for each MediaPipe
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Solution:
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<!-- []() in the first cell is needed to preserve table formatting in GitHub Pages. -->
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<!-- Whenever this table is updated, paste a copy to solutions/solutions.md. -->
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* **MediaPipe Tasks**: Cross-platform APIs and libraries for deploying
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solutions. [Learn
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more](https://developers.google.com/mediapipe/solutions/tasks).
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* **MediaPipe models**: Pre-trained, ready-to-run models for use with each
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solution.
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[]() | [Android](https://google.github.io/mediapipe/getting_started/android) | [iOS](https://google.github.io/mediapipe/getting_started/ios) | [C++](https://google.github.io/mediapipe/getting_started/cpp) | [Python](https://google.github.io/mediapipe/getting_started/python) | [JS](https://google.github.io/mediapipe/getting_started/javascript) | [Coral](https://github.com/google/mediapipe/tree/master/mediapipe/examples/coral/README.md)
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:---------------------------------------------------------------------------------------- | :-------------------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------------: | :-----------------------------------------------------------: | :--------------------------------------------------------------------:
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[Face Detection](https://google.github.io/mediapipe/solutions/face_detection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
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[Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh) | ✅ | ✅ | ✅ | ✅ | ✅ |
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[Iris](https://google.github.io/mediapipe/solutions/iris) | ✅ | ✅ | ✅ | | |
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[Hands](https://google.github.io/mediapipe/solutions/hands) | ✅ | ✅ | ✅ | ✅ | ✅ |
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[Pose](https://google.github.io/mediapipe/solutions/pose) | ✅ | ✅ | ✅ | ✅ | ✅ |
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[Holistic](https://google.github.io/mediapipe/solutions/holistic) | ✅ | ✅ | ✅ | ✅ | ✅ |
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[Selfie Segmentation](https://google.github.io/mediapipe/solutions/selfie_segmentation) | ✅ | ✅ | ✅ | ✅ | ✅ |
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[Hair Segmentation](https://google.github.io/mediapipe/solutions/hair_segmentation) | ✅ | | ✅ | | |
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[Object Detection](https://google.github.io/mediapipe/solutions/object_detection) | ✅ | ✅ | ✅ | | | ✅
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[Box Tracking](https://google.github.io/mediapipe/solutions/box_tracking) | ✅ | ✅ | ✅ | | |
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[Instant Motion Tracking](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | ✅ | | | | |
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[Objectron](https://google.github.io/mediapipe/solutions/objectron) | ✅ | | ✅ | ✅ | ✅ |
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[KNIFT](https://google.github.io/mediapipe/solutions/knift) | ✅ | | | | |
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[AutoFlip](https://google.github.io/mediapipe/solutions/autoflip) | | | ✅ | | |
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[MediaSequence](https://google.github.io/mediapipe/solutions/media_sequence) | | | ✅ | | |
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[YouTube 8M](https://google.github.io/mediapipe/solutions/youtube_8m) | | | ✅ | | |
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These tools let you customize and evaluate solutions:
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See also
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[MediaPipe Models and Model Cards](https://google.github.io/mediapipe/solutions/models)
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for ML models released in MediaPipe.
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* **MediaPipe Model Maker**: Customize models for solutions with your data.
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[Learn more](https://developers.google.com/mediapipe/solutions/model_maker).
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* **MediaPipe Studio**: Visualize, evaluate, and benchmark solutions in your
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browser. [Learn
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more](https://developers.google.com/mediapipe/solutions/studio).
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## Getting started
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### Legacy solutions
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To start using MediaPipe
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[solutions](https://google.github.io/mediapipe/solutions/solutions) with only a few
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lines code, see example code and demos in
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[MediaPipe in Python](https://google.github.io/mediapipe/getting_started/python) and
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[MediaPipe in JavaScript](https://google.github.io/mediapipe/getting_started/javascript).
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We have ended support for [these MediaPipe Legacy Solutions](https://developers.google.com/mediapipe/solutions/guide#legacy)
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as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to
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a new MediaPipe Solution. See the [Solutions guide](https://developers.google.com/mediapipe/solutions/guide#legacy)
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for details. The [code repository](https://github.com/google/mediapipe/tree/master/mediapipe)
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and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be
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provided on an as-is basis.
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To use MediaPipe in C++, Android and iOS, which allow further customization of
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the [solutions](https://google.github.io/mediapipe/solutions/solutions) as well as
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building your own, learn how to
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[install](https://google.github.io/mediapipe/getting_started/install) MediaPipe and
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start building example applications in
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[C++](https://google.github.io/mediapipe/getting_started/cpp),
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[Android](https://google.github.io/mediapipe/getting_started/android) and
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[iOS](https://google.github.io/mediapipe/getting_started/ios).
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For more on the legacy solutions, see the [documentation](https://github.com/google/mediapipe/tree/master/docs/solutions).
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The source code is hosted in the
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[MediaPipe Github repository](https://github.com/google/mediapipe), and you can
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run code search using
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[Google Open Source Code Search](https://cs.opensource.google/mediapipe/mediapipe).
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## Framework
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## Publications
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To start using MediaPipe Framework, [install MediaPipe
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Framework](https://developers.google.com/mediapipe/framework/getting_started/install)
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and start building example applications in C++, Android, and iOS.
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[MediaPipe Framework](https://developers.google.com/mediapipe/framework) is the
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low-level component used to build efficient on-device machine learning
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pipelines, similar to the premade MediaPipe Solutions.
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Before using MediaPipe Framework, familiarize yourself with the following key
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[Framework
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concepts](https://developers.google.com/mediapipe/framework/framework_concepts/overview.md):
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* [Packets](https://developers.google.com/mediapipe/framework/framework_concepts/packets.md)
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* [Graphs](https://developers.google.com/mediapipe/framework/framework_concepts/graphs.md)
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* [Calculators](https://developers.google.com/mediapipe/framework/framework_concepts/calculators.md)
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## Community
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* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe
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users.
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* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
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community discussion around MediaPipe.
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* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
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curated list of awesome MediaPipe related frameworks, libraries and
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software.
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## Contributing
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We welcome contributions. Please follow these
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[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
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We use GitHub issues for tracking requests and bugs. Please post questions to
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the MediaPipe Stack Overflow with a `mediapipe` tag.
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## Resources
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### Publications
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* [Bringing artworks to life with AR](https://developers.googleblog.com/2021/07/bringing-artworks-to-life-with-ar.html)
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in Google Developers Blog
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@@ -102,7 +125,8 @@ run code search using
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* [SignAll SDK: Sign language interface using MediaPipe is now available for
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developers](https://developers.googleblog.com/2021/04/signall-sdk-sign-language-interface-using-mediapipe-now-available.html)
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in Google Developers Blog
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* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
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* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on
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Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
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in Google AI Blog
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* [Background Features in Google Meet, Powered by Web ML](https://ai.googleblog.com/2020/10/background-features-in-google-meet.html)
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in Google AI Blog
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@@ -130,43 +154,6 @@ run code search using
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in Google AI Blog
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* [MediaPipe: A Framework for Building Perception Pipelines](https://arxiv.org/abs/1906.08172)
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## Videos
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### Videos
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* [YouTube Channel](https://www.youtube.com/c/MediaPipe)
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## Events
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* [MediaPipe Seattle Meetup, Google Building Waterside, 13 Feb 2020](https://mediapipe.page.link/seattle2020)
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* [AI Nextcon 2020, 12-16 Feb 2020, Seattle](http://aisea20.xnextcon.com/)
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* [MediaPipe Madrid Meetup, 16 Dec 2019](https://www.meetup.com/Madrid-AI-Developers-Group/events/266329088/)
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* [MediaPipe London Meetup, Google 123 Building, 12 Dec 2019](https://www.meetup.com/London-AI-Tech-Talk/events/266329038)
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* [ML Conference, Berlin, 11 Dec 2019](https://mlconference.ai/machine-learning-advanced-development/mediapipe-building-real-time-cross-platform-mobile-web-edge-desktop-video-audio-ml-pipelines/)
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* [MediaPipe Berlin Meetup, Google Berlin, 11 Dec 2019](https://www.meetup.com/Berlin-AI-Tech-Talk/events/266328794/)
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* [The 3rd Workshop on YouTube-8M Large Scale Video Understanding Workshop,
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Seoul, Korea ICCV
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2019](https://research.google.com/youtube8m/workshop2019/index.html)
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* [AI DevWorld 2019, 10 Oct 2019, San Jose, CA](https://aidevworld.com)
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* [Google Industry Workshop at ICIP 2019, 24 Sept 2019, Taipei, Taiwan](http://2019.ieeeicip.org/?action=page4&id=14#Google)
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([presentation](https://docs.google.com/presentation/d/e/2PACX-1vRIBBbO_LO9v2YmvbHHEt1cwyqH6EjDxiILjuT0foXy1E7g6uyh4CesB2DkkEwlRDO9_lWfuKMZx98T/pub?start=false&loop=false&delayms=3000&slide=id.g556cc1a659_0_5))
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* [Open sourced at CVPR 2019, 17~20 June, Long Beach, CA](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe)
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## Community
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* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
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curated list of awesome MediaPipe related frameworks, libraries and software
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* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe users
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* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
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community discussion around MediaPipe
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## Alpha disclaimer
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MediaPipe is currently in alpha at v0.7. We may be still making breaking API
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changes and expect to get to stable APIs by v1.0.
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## Contributing
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We welcome contributions. Please follow these
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[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
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We use GitHub issues for tracking requests and bugs. Please post questions to
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the MediaPipe Stack Overflow with a `mediapipe` tag.
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